Abstract
Aims
Root system architecture traits (RSAT) are crucial for crop productivity, especially under drought and low soil fertility. The “shovelomics” method of field excavation of mature root crowns followed by manual phenotyping enables a relatively high throughput as needed for breeding and quantitative genetics. We aimed to develop a new sampling protocol in combination with digital imaging and new software.
Methods
Sampled rootstocks were split lengthwise, photographed under controlled illumination in an imaging tent and analysed using Root Estimator for Shovelomics Traits (REST). A set of 33 diverse maize hybrids, grown at 46 and 192 kg N ha−1, was used to evaluate the method and software.
Results
Splitting of the crowns enhanced soil removal and enabled access to occluded traits: REST-derived median gap size correlated negatively (r = −0.62) with lateral root density based on counting. The manually measured root angle correlated with the image-derived root angle (r = 0.89) and the horizontal extension of the root system (r = 0.91). The heritabilities of RSAT ranged from 0.45 to 0.81, comparable to heritabilities of plant height and leaf biomass.
Conclusion
The combination of the novel crown splitting method, combined with imaging under controlled illumination followed by automatic analysis with REST, allowed for higher throughput while maintaining precision. The REST Software is available as supplement. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000100285Publication status
publishedExternal links
Journal / series
Plant and SoilVolume
Pages / Article No.
Publisher
SpringerSubject
Root system architecture; Maize; Automated phenotyping; Image processing; HeritabilityOrganisational unit
03894 - Walter, Achim / Walter, Achim
Funding
289300 - Enhancing resource Uptake from Roots under stress in cereal crops (EC)
Notes
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.More
Show all metadata